# Copyright 2020 The Kubeflow Authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Tests for kfp.v2.dsl.container_op"""
import unittest

from kfp.dsl import _container_op
from kfp.pipeline_spec import pipeline_spec_pb2

from google.protobuf import text_format
from google.protobuf import json_format

_EXPECTED_CONTAINER_WITH_RESOURCE = """
resources {
  cpu_limit: 1.0
  memory_limit: 1.0
  accelerator {
    type: 'NVIDIA_TESLA_K80'
    count: 1
  }
}
"""

# Shorthand for PipelineContainerSpec
_PipelineContainerSpec = pipeline_spec_pb2.PipelineDeploymentConfig.PipelineContainerSpec


class ContainerOpTest(unittest.TestCase):

  def test_chained_call_resource_setter(self):
    task = _container_op.ContainerOp(name='test_task', image='python:3.7')
    task.container_spec = _PipelineContainerSpec()
    (task.
     set_cpu_limit('1').
     set_memory_limit('1G').
     add_node_selector_constraint(
        'cloud.google.com/gke-accelerator',
        'nvidia-tesla-k80').
     set_gpu_limit(1))

    expected_container_spec = text_format.Parse(
        _EXPECTED_CONTAINER_WITH_RESOURCE, _PipelineContainerSpec())

    self.assertDictEqual(json_format.MessageToDict(task.container_spec),
                         json_format.MessageToDict(expected_container_spec))


if __name__ == '__main__':
  unittest.main()
